Review of interim clinical trial data has many potential advantages: an ethical attractiveness with potentially fewer patients exposed to possibly harmful or ineffective therapies; economic savings with smaller expected sample sizes and shorter trial durations saving money, time, and other resources; and public health advantages as answers are available more quickly to the medical community. Reviewing interim data however poses two major scientific concerns: statistical (e.g., error control) and operational. Many recent developments in adaptive design methodology are available to address statistical concerns and Data Monitoring Committees are used to help address operational concerns. Yet many challenges still exist and interim decision-making remains sub-optimal. I will discuss examples of trials with interim adaptations, discuss methods using prediction for more flexible and informative interim decision-making, and present ideas for revising our traditional approaches to DMCs (scientific and operational) to maximize trial efficiency and improve decision-making while maintaining trial integrity.